Taken together, our results demonstrate that viral-mediated disruption of Rac1 expression in ventral horn motor neurons can mitigate dendritic spine morphological correlates of neuronal hyperexcitability, and reverse hyperreflexia associated with spasticity after SCI. Finally, our findings provide evidence of a putative mechanistic relationship between motor neuron dendritic spine dysgenesis and SCI-induced spasticity.Persistence of wild Pacific oyster, Magallana gigas, also known as Crassostrea gigas, has been increasingly reported across Northern European waters in recent years. While reproduction is inhibited by cold waters, recent warm summer temperature has increased the frequency of spawning events. Although correlation between the increasing abundance of Pacific oyster reefs in Northern European waters and climate change is documented, persistence of wild populations may also be influenced by external recruitment from farmed populations and other wild oyster populations, as well as on competition for resources with aquaculture sites. Our understanding of the combined impact of the spawning frequency, external recruitment, and competition on wild population persistence is limited. This study applied an age-structured model, based on ordinary differential equations, to describe an oyster population under discrete temperature-related dynamics. The impact of more frequent spawning events, external recruitment, and changes in carrying capacity on Pacific oyster density were simulated and compared under theoretical scenarios and two case studies in Southern England. Results indicate that long term persistence of wild oyster populations towards carrying capacity requires a high frequency of spawning events but that in the absence of spawning, external recruitment from farmed populations and other wild oyster populations may act to prevent extinction and increase population density. However, external recruitment sources may be in competition with the wild population so that external recruitment is associated with a reduction in wild population density. The implications of model results are discussed in the context of wild oyster population management.Light/dark cycling is an inherent condition of outdoor microalgae cultivation, but is often unfavorable for lipid accumulation. This study aims to identify promising targets for metabolic engineering of improved lipid accumulation under outdoor conditions. Consequently, the lipid-rich mutant Chlamydomonas sp. KOR1 was developed through light/dark-conditioned screening. During dark periods with depressed CO2 fixation, KOR1 shows rapid carbohydrate degradation together with increased lipid and carotenoid contents. KOR1 was subsequently characterized with extensive mutation of the ISA1 gene encoding a starch debranching enzyme (DBE). Dynamic time-course profiling and metabolomics reveal dramatic changes in KOR1 metabolism throughout light/dark cycles. During light periods, increased flux from CO2 through glycolytic intermediates is directly observed to accompany enhanced formation of small starch-like particles, which are then efficiently repartitioned in the next dark cycle. This study demonstrates that disruption of DBE can improve biofuel production under light/dark conditions, through accelerated carbohydrate repartitioning into lipid and carotenoid.A key challenge to gaining insight into complex systems is inferring nonlinear causal directional relations from observational time-series data. Specifically, estimating causal relationships between interacting components in large systems with only short recordings over few temporal observations remains an important, yet unresolved problem. Here, we introduce large-scale nonlinear Granger causality (lsNGC) which facilitates conditional Granger causality between two multivariate time series conditioned on a large number of confounding time series with a small number of observations. By modeling interactions with nonlinear state-space transformations from limited observational data, lsNGC identifies casual relations with no explicit a priori assumptions on functional interdependence between component time series in a computationally efficient manner. Additionally, our method provides a mathematical formulation revealing statistical significance of inferred causal relations. We extensively study the ability of lsNGC in inferring directed relations from two-node to thirty-four node chaotic time-series systems. Our results suggest that lsNGC captures meaningful interactions from limited observational data, where it performs favorably when compared to traditionally used methods. Finally, we demonstrate the applicability of lsNGC to estimating causality in large, real-world systems by inferring directional nonlinear, causal relationships among a large number of relatively short time series acquired from functional Magnetic Resonance Imaging (fMRI) data of the human brain.Extreme responders to anticancer therapy are rare among advanced breast cancer patients. Researchers, however, have yet to investigate treatment responses therein on the whole exome level. We performed whole exome analysis to characterize the genomic landscape of extreme responders among metastatic breast cancer patients. Clinical samples were obtained from breast cancer patients who showed exceptional responses to anti-HER2 therapy or hormonal therapy and from those who did not. https://www.selleckchem.com/products/sch-900776.html Matched breast tumor tissue (somatic DNA) and blood samples (germline DNA) were collected from a total of 30 responders and 15 non-responders. Whole exome sequencing using Illumina HiSeq2500 was performed for all 45 patients (90 samples). Somatic single nucleotide variants (SNVs), indels, and copy number variants (CNVs) were identified for the genomes of each patient. Group-specific somatic variants and mutational burden were statistically analyzed. Sequencing of cancer exomes for all patients revealed 1839 somatic SNVs (1661 missense, 120 nonsense, 43 splice-site, 15 start/stop-lost) and 368 insertions/deletions (273 frameshift, 95 in-frame), with a median of 0.7 mutations per megabase (range, 0.08 to 4.2 mutations per megabase). Responders harbored a significantly lower nonsynonymous mutational burden (median, 26 vs. 59, P?=?0.02) and fewer CNVs (median 13.6 vs. 97.7, P?=?0.05) than non-responders. Multivariate analyses of factors influencing progression-free survival showed that a high mutational burden and visceral metastases were significantly related with disease progression. Extreme responders to treatment for metastatic breast cancer are characterized by fewer nonsynonymous mutations and CNVs.